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Beautifulsoup Extract Text

• April 16, 2022
• 0

Using BeautifulSoup to extract text without tags – Stack Overflow

I think you can get it using
>>> html = “””

YOB: 1987
RACE: WHITE
GENDER: FEMALE
HEIGHT: 5’05”
WEIGHT: 118
EYE COLOR: GREEN
HAIR COLOR: BROWN

“””
>>> from bs4 import BeautifulSoup
>>> soup = BeautifulSoup(html)
>>> print
YOB: 1987
RACE: WHITE
GENDER: FEMALE
HEIGHT: 5’05”
WEIGHT: 118
EYE COLOR: GREEN
HAIR COLOR: BROWN
Or if you want to explore it, you can use. contents:
>>> p = (‘p’)
>>> from pprint import pprint
>>> pprint(ntents)
[u’n’,
YOB:,
u’ 1987′,

,
u’n’,
RACE:,
u’ WHITE’,
GENDER:,
u’ FEMALE’,
HEIGHT:,
u” 5’05””,
WEIGHT:,
u’ 118′,
EYE COLOR:,
u’ GREEN’,
HAIR COLOR:,
u’ BROWN’,
u’n’]
and filter out the necessary items from the list:
>>> data = dict(zip([ for x in ntents[1::4]], [() for x in ntents[2::4]]))
>>> pprint(data)
{u’EYE COLOR:’: u’GREEN’,
u’GENDER:’: u’FEMALE’,
u’HAIR COLOR:’: u’BROWN’,
u’HEIGHT:’: u”5’05””,
u’RACE:’: u’WHITE’,
u’WEIGHT:’: u’118′,
u’YOB:’: u’1987′}

Extract text from a webpage using BeautifulSoup and Python

If you’re going to spend time crawling the web, one task you might encounter is stripping out visible text content from HTML.
If you’re working in Python, we can accomplish this using BeautifulSoup.
Setting up the extraction
To start, we’ll need to get some HTML. I’ll use Troy Hunt’s recent blog post about the “Collection #1″ Data Breach.
Here’s how you might download the HTML:
import requests
url = ”
res = (url)
html_page = ntent
Now, we have the HTML.. but there will be a lot of clutter in there. How can we extract the information we want?
Creating the “beautiful soup”
We’ll use Beautiful Soup to parse the HTML as follows:
from bs4 import BeautifulSoup
soup = BeautifulSoup(html_page, ”)
Finding the text
BeautifulSoup provides a simple way to find text content (i. e. non-HTML) from the HTML:
text = nd_all(text=True)
However, this is going to give us some information we don’t want.
Look at the output of the following statement:
set([ for t in text])
# {‘label’, ‘h4’, ‘ol’, ‘[document]’, ‘a’, ‘h1’, ‘noscript’, ‘span’, ‘header’, ‘ul’, ‘html’, ‘section’, ‘article’, ’em’, ‘meta’, ‘title’, ‘body’, ‘aside’, ‘footer’, ‘div’, ‘form’, ‘nav’, ‘p’, ‘head’, ‘link’, ‘strong’, ‘h6’, ‘br’, ‘li’, ‘h3’,
‘h5’, ‘input’, ‘blockquote’, ‘main’, ‘script’, ‘figure’}
There are a few items in here that we likely do not want:
[document]
noscript
header
html
meta
head
input
script
For the others, you should check to see which you want.
Extracting the valuable text
Now that we can see our valuable elements, we can build our output:
output = ”
blacklist = [
‘[document]’,
‘noscript’,
‘header’,
‘html’,
‘meta’,
‘head’,
‘input’,
‘script’,
# there may be more elements you don’t want, such as “style”, etc. ]
for t in text:
if not in blacklist:
output += ‘{} ‘(t)
The full script
Finally, here’s the full Python script to get text from a webpage:
print(output)
Improvements
If you look at output now, you’ll see that we have some things we don’t want.
There’s some text from the header:
Home n n n Workshops n n n Speaking n n n Media n n
n About n n n Contact n n n Sponsor n n n n n n n n n n n n n n n n n n n n n n n n n n n n n Sponsored by:
And there’s also some text from the footer:
n n n n n n Weekly Update 122 n n n n n Weekly Update 121 n n n n n n n n Subscribe n n n n n n n n n n Subscribe Now! n n n n rn Send new blog posts: n daily n
weekly n n n n Hey, just quickly confirm you’re not a robot: n Submitting… n Got it! Check your email, click the confirmation
link I just sent you and we’re done. n n n n n n n n Copyright 2019, Troy Hunt n This work is licensed under a Creative Commons Attribution 4. 0 International License. In other words, share generously but provide attribution. n n n Disclaimer n Opinions expressed here are my own and may not reflect those of people I work with, my mates, my wife, the kids etc. Unless I’m quoting someone, they’re just my own views. n n n Published with Ghost n This site runs entirely on Ghost and is made possible thanks to their kind support. Read more about why I chose to use Ghost. n n n n n n n n n n n n n n n n n n n n n n n n n n
n n n n n ‘
If you’re just extracting text from a single site, you can probably look at the HTML and find a way to parse out only the valuable content from the page.
Unfortunately, the internet is a messy place and you’ll have a tough time finding consensus on HTML semantics.
Good luck!

BeautifulSoup – Scraping Paragraphs from HTML

In this article, we will discuss how to scrap paragraphs from HTML using Beautiful SoupMethod 1: using bs4 and urllib. Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics. To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level CourseModule Needed:bs4: Beautiful Soup(bs4) is a Python library for pulling data out of HTML and XML files. For installing the module-pip install urllib is a package that collects several modules for working with URLs. It can also be installed the same way, it is most of the in-built in the environment install urllibThe html file contains several tags and like the anchor tag , span tag , paragraph tag

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